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Record W4283206690 · doi:10.2514/6.2022-3518

Effect of Leading Edge Tubercles on Tilt-Wing Transition

2022· article· en· W4283206690 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAIAA AVIATION 2022 Forum · 2022
Typearticle
Languageen
FieldEngineering
TopicBiomimetic flight and propulsion mechanisms
Canadian institutionsRoyal Military College of Canada
Fundersnot available
KeywordsWingTilt (camera)Enhanced Data Rates for GSM EvolutionTransition (genetics)PhysicsComputer scienceGeometryOpticsMathematicsComputer visionBiologyGenetics

Abstract

fetched live from OpenAlex

View Video Presentation: https://doi.org/10.2514/6.2022-3518.vid The transition of tilt-wing aircraft involves a wide range of angles of attack, effectively ranging from 0 to 75 degrees. Leading edge tubercles can improve lift performance by improving flow attachment at high angles of attack. In this experimental work, the effect of a propeller slipstream on the aerodynamic performance of wings with a straight leading edge and three tubercle leading edges were evaluated. The position of the propeller with respect to the wing was varied to obtain the optimal propeller position of each wing for tilt-wing transition. The presence of tubercles on the leading enhanced the performance of the blown wing in the post-stall regime. The effect of the tubercles on the transition corridor was also analyzed. The presence of tubercles widened the lower bound of the transition corridor.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.165
Threshold uncertainty score0.803

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.005
GPT teacher head0.210
Teacher spread0.205 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it